Translation method and translation system for translating input expression into expression in another language

ABSTRACT

A translation system includes translation subsystems by a plurality of translation policies with different translation output tendencies, performs forward translation and reverse translation by a consistent translation policy, and ranks the plurality of translation policies based on a similarity between the reverse translation sentences and the original sentence. As a result, a translation policy that best matches each input object to be translated is selected from the plurality of translation policies for each input sentence and, as a consequence, it is possible to cover a wide range of natures of sentences to be translated.

BACKGROUND

1. Technical Field

The present disclosure relates to a translation method and a translationsystem that translate an input expression into an expression in anotherlanguage.

2. Description of the Related Art

There is a system that outputs a plurality of translation sentences whenperforming machine translation from a first language to a secondlanguage. Moreover, there is a system that automatically evaluates thereliability of the translation sentence. In Japanese Unexamined PatentApplication Publication No. 2006-53683, a technique of outputting N-besttranslation sentences in statistical machine translation is disclosed.In Japanese Unexamined Patent Application Publication No. 2014-78132, atechnique of calculating the degree of similarity between a reversetranslation sentence obtained by performing reverse translation (from asecond language to a first language) of a translation sentence and apre-translation original sentence and using the degree of similarity forthe evaluation of the reliability of the translation sentence isdisclosed.

SUMMARY

However, a further study has been required to improve the accuracy oftranslation.

In one general aspect, the techniques disclosed here feature atranslation method including: obtaining an original sentence to betranslated; performing bidirectional translation by obtaining atranslation sentence corresponding to the original sentence byperforming forward translation and obtaining a reverse translationsentence from the translation sentence by performing reversetranslation, for each of a plurality of translation policies; rankingthe translation policies based on the degree of similarity between thereverse translation sentences by the plurality of translation policiesand the original sentence; and displaying the translation sentences bythe plurality of translation policies in a state in which eachtranslation sentence is related to the ranking, in which the forwardtranslation and the reverse translation are performed consistently foreach translation policy.

It is possible to perform highly accurate translation.

It should be noted that general or specific embodiments may beimplemented as a system, a method, an integrated circuit, a computerprogram, a storage medium, or any selective combination thereof.

Additional benefits and advantages of the disclosed embodiments willbecome apparent from the specification and drawings. The benefits and/oradvantages may be individually obtained by the various embodiments andfeatures of the specification and drawings, which need not all beprovided in order to obtain one or more of such benefits and/oradvantages.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A to 1C depict the overview of a translation system in anembodiment;

FIGS. 2A and 2B are block diagrams depicting the schematic configurationof the translation system in this embodiment;

FIG. 3 is a flowchart of the translation system in this embodiment;

FIG. 4 is a table for explaining the effect obtained by combining aplurality of policies of the translation system in this embodiment;

FIG. 5 is a table illustrating the difference in an accuracy ratebetween a single policy and the combined use of policies of thetranslation system in this embodiment;

FIG. 6 is a first translation example performed by the translationsystem in this embodiment;

FIG. 7 is a second translation example performed by the translationsystem in this embodiment;

FIG. 8 is an example of the display of the first translation exampleperformed by the translation system in this embodiment;

FIG. 9 is a diagram depicting a service type 1 (a company's data centertype);

FIG. 10 is a diagram depicting a service type 2 (an IaaS use type);

FIG. 11 is a diagram depicting a service type 3 (a PaaS use type); and

FIG. 12 is a diagram depicting a service type 4 (an SaaS use type).

DETAILED DESCRIPTION (Underlying Knowledge Forming Basis of the PresentDisclosure)

Translation techniques adopting various approaches such as rule-basedtranslation and bilingual corpus-based translation have been studied.However, in translation service, as the nature of a sentence to betranslated, for a style (written language/spoken language), the field ofcontents (medical care, phrases for tourists, and patent), the length ofa sentence, the complexity of syntax, the specialized nature of a term,and so forth, there are various needs. No study on technical solutionsto cover these various needs has been conducted.

For example, with the method proposed in Japanese Unexamined PatentApplication Publication No. 2006-53683, since it is possible to obtain Ntranslation sentences within an N-best framework, there is a possibilitythat, even when the first result is incorrect, a correct translation canbe extracted from the lower-order candidates. Moreover, with the methodproposed in Japanese Unexamined Patent Application Publication No.2014-78132, it is possible to evaluate the reliability of a translationsentence in the framework of reverse translation. It appears to be ableto improve the accuracy by combining these techniques. However, in aconfiguration obtained by combining these techniques, since Ntranslation results obtained by one translation policy are similar toone another, even when the ranking is changed by using the reversetranslation results, the configuration has less room to improve theaccuracy as compared to the original accuracy of 1-best translation.

In order to solve such a problem, a translation method includes:obtaining an original sentence to be translated; performingbidirectional translation by obtaining a translation sentencecorresponding to the original sentence by performing forward translationand obtaining a reverse translation sentence from the translationsentence by performing reverse translation, for each of a plurality oftranslation policies; ranking the translation policies based on thedegree of similarity between the reverse translation sentences by theplurality of translation policies and the original sentence; anddisplaying the translation sentences by the plurality of translationpolicies in a state in which each translation sentence is related to theranking, in which the forward translation and the reverse translationare performed consistently for each translation policy.

Moreover, in the performing bidirectional translation, if the originalsentence is written in a first language, a first translation sentencemay be obtained by translating the original sentence into a secondlanguage by a first translation policy, a first reverse translationsentence may be obtained by performing reverse translation of the firsttranslation sentence into the first language by the first translationpolicy, a second translation sentence may be obtained by translating theoriginal sentence into the second language by a second translationpolicy, and a second reverse translation sentence may be obtained byperforming reverse translation of the second translation sentence intothe first language by the second translation policy.

Furthermore, in the ranking, the first degree of similarity between theoriginal sentence and the first reverse translation sentence may becalculated, the second degree of similarity between the originalsentence and the second reverse translation sentence may be calculated,and the first degree of similarity and the second degree of similaritymay be compared and the first translation sentence and the secondtranslation sentence may be ranked in descending order of degree ofsimilarity.

In addition, in the displaying, the first translation sentence and thesecond translation sentence ranked in the ranking may be displayed insuch a way that a translation sentence in a higher rank is displayed inan upper portion.

Moreover, the degree of similarity may be a value obtained bysubtracting the number of disparities in units of words between thereverse translation sentence and the original sentence from the numberof matches in units of words between the reverse translation sentenceand the original sentence.

Furthermore, the translation policy may be an algorithm reflecting adesign guide in machine translation.

In addition, a translation system includes: an input portion thatobtains an original sentence as an input; a plurality of bidirectionaltranslation subsystems corresponding to a plurality of differenttranslation policies; a translation policy ranker that ranks theplurality of translation policies; and a result displaying portion thatdisplays a translation sentence in accordance with the result of rankingof the translation policies, in which the bidirectional translationsubsystems each obtain, for each translation policy, a translationsentence corresponding to the original sentence and a reversetranslation sentence corresponding to the translation sentence, and thetranslation policy ranker ranks the translation policies based on thedegree of similarity between a plurality of the reverse translationsentences and the original sentence.

As a result, a translation policy that best matches each input object tobe translated is selected for each input sentence from among a pluralityof translation policies, which makes it possible to cover the nature ofthe sentence to be translated widely as a whole.

Here, the translation policy is an algorithm reflecting a design guideof machine translation. Incidentally, a designer does not have to beconscious of this design guide. For example, as the machine translationmethod, there are rule-based translation and statistics-basedtranslation, which have different specialized objects to be translated.Rule-based translation is a method of converting an input sentence inone language into an output sentence in another language by amanually-written rule. Statistics-based translation is a method ofconverting an input sentence in one language into an output sentence inanother language by using a translation rule calculated by statisticalstudy using a corpus of two languages. Moreover, since translations bythe same statistics-based translation have different specialized objectsto be translated if different corpora based on which the amount ofstatistics is determined are used, these translations are examplesadopting different policies. Furthermore, various biases, such as thedifference between a case in which a word is used as a basic unit oftranslation and a case in which a phrase is used as a basic unit oftranslation, which vary the output tendency can become a difference inpolicy. In general, the translation policies are integrated into onepolicy which the designer believes the best, but one policy has alimitation in accuracy for various inputs.

Incidentally, an embodiment which will be described below illustratesone specific example of the present disclosure. The numerical values,shapes, component elements, steps, order of steps, and so forth whichare described in the following embodiment are mere examples and are notmeant to limit the present disclosure. Moreover, of the componentelements in the following embodiment, a component element which is notdescribed in an independent claim describing the broadest concept of thepresent disclosure is described as an arbitrary component element.Furthermore, in all the embodiments, it is also possible to combine thecontents thereof.

(Overview of Service which is Provided)

In FIG. 1A, an overview of an information providing system in thisembodiment is depicted.

A group 100 is, for example, a company, an organization, or a householdand the size thereof does not matter. In the group 100, a device A and adevice B which are a plurality of devices 101 and a home gateway 102 arepresent. As the plurality of devices 101, there are a device (forexample, a smartphone, a PC, a TV, or the like) which is connectable tothe Internet and a device (for example, a lighting fixture, a washingmachine, a refrigerator, or the like) which is not connectable to theInternet by itself. There may be a device that is a device which is notconnectable to the Internet by itself but is connectable to the Internetvia the home gateway 102. Moreover, in the group 100, a user 10 who usesthe plurality of devices 101 is present.

In a data center operating company 110, a cloud server 111 is present.The cloud server 111 is a virtualized server that cooperates withvarious devices via the Internet. The cloud server 111 mainly manages,for example, big data that is difficult to be handled by a normaldatabase management tool or the like. The data center operating company110 performs the data management and the management of the cloud server111 and operates a data center performing such management, for example.The details of the service performed by the data center operatingcompany 110 will be described later. Here, the data center operatingcompany 110 is not limited to a company that performs only the datamanagement, the operation of the cloud server 111, and so forth. Forexample, if a device maker that develops and produces one of theplurality of devices 101 also performs the data management, themanagement of the cloud server 111, and so forth, the device makercorresponds to the data center operating company 110 (FIG. 1B).Moreover, the data center operating company 110 is not limited to asingle company. For example, if the device maker and the othermanagement company perform the data management and the operation of thecloud server 111 in cooperation with each other or share the datamanagement and the operation of the cloud server 111, it is assumed thatboth or any one of the device maker and the other management companycorresponds to the data center operating company 110 (FIG. 1C).

A service provider 120 has a server 121. The size of the server 121 heredoes not matter and examples of the server 121 include memory in apersonal computer. Moreover, sometimes the service provider 120 does nothave the server 121.

Incidentally, in the above-described service, the home gateway 102 isnot indispensable. For example, if the cloud server 111 performs all thedata management, the home gateway 102 is not necessary. Moreover, like acase in which all the devices in the household are connected to theInternet, there is a case in which a device which is not connectable tothe Internet by itself is not present.

Next, the flow of information in the above-described service will bedescribed.

First, the device A or the device B of the group 100 transmits each loginformation to the cloud server 111 of the data center operating company110. The cloud server 111 accumulates the log information of the deviceA or the device B (part (a) of FIG. 1A). Here, the log information isinformation indicating the operation status, the operation date andtime, and so forth of the plurality of devices 101. Examples of the loginformation include a history of television viewing, information onprogrammed recording performed by a recorder, the operation date andtime and the amount of laundry of a washing machine, the opening andclosing date and time and the number of opening and closing operationsof a refrigerator, and so forth, but the log information is not limitedthereto; the log information refers to all the information which can beobtained from all devices. The log information is sometimes provideddirectly to the cloud server 111 from the plurality of devices 101themselves via the Internet. Moreover, the log information may betemporarily accumulated in the home gateway 102 from the plurality ofdevices 101 and then provided to the cloud server 111 from the homegateway 102.

Next, the cloud server 111 of the data center operating company 110provides the accumulated log information to the service provider 120 ina fixed unit. Here, the unit may be a unit by which the data centeroperating company 110 can organize the accumulated information andprovide the organized information to the service provider 120 or a unitrequested by the service provider 120. The unit may not be a fixed unit,and the amount of information to be provided may vary depending on thesituation. The log information is stored in the server 121 of theservice provider 120 if necessary (part (b) of FIG. 1A). Then, theservice provider 120 organizes the log information to obtain informationthat suits to a service to be provided to the user and provides theservice to the user. The user to which the service is provided may bethe user 10 who uses the plurality of devices 101 or an external user20. As the method for providing the service to the user, for example,the service may be provided directly to the user from the serviceprovider 120 (part (b) and part (e) of FIG. 1A). Moreover, as the methodfor providing the service to the user, for example, the service may beprovided to the user via the cloud server 111 of the data centeroperating company 110 again (part (c) and part (d) of FIG. 1A).Furthermore, the cloud server 111 of the data center operating company110 may organize the log information to obtain information that suits toa service to be provided to the user and provide the information to theservice provider 120.

Incidentally, the user 10 and the user 20 may be different users or oneand the same user.

First Embodiment

FIGS. 2A and 2B are block diagrams depicting a schematic configurationin this embodiment and depict an example of a system that performsJapanese-English translation.

This translation system includes an input portion 1000, a processingportion 2000, and an output displaying portion 3000. Incidentally, theseconfigurations do not necessarily have to be provided collectively inone apparatus and may be distributed over any apparatuses such as thedevices 101, the cloud server 111, the server 121, and so forth depictedin FIGS. 1A to 1C. For example, each device 101 (such as a smartphone)may include the input portion 1000 and the output displaying portion3000, and the cloud server 111 (or the server 121) may include theprocessing portion 2000. In this case, by performing transmission andreception of information between the devices provided with acommunication unit, processing of FIGS. 2A and 2B and FIG. 3, which willbe described below, is implemented.

In FIG. 2A, the input portion 1000 accepts an input of an originalsentence (Japanese) 201 to be translated and outputs the originalsentence (Japanese) 201 to the processing portion 2000. Here, the inputportion 1000 is, for example, a touch panel-type text input unitprovided in the device 101. In this case, the user inputs, via a touchpanel, a sentence which the user desires to translate. Then, the inputsentence is transmitted to the processing portion 2000 of the cloudserver 111 via an unillustrated communication unit. Incidentally, theinput portion 1000 is not necessarily limited to the touch panel-typetext input unit; in the case of a mobile terminal provided with aphysical input button, the input button corresponds to the input portion1000 and, in the case of a PC or the like, a keyboard or a mousecorresponds to the input portion 1000. Moreover, if the device 101includes the processing portion 2000, there is no need to transmit thetext information input by the input portion 1000 to the cloud server 111or the like. Furthermore, the input portion 1000 is not limited to thetext input unit and may be a sound pickup apparatus (a microphone) orthe like for voice recognition. In this case, in a voice recognitionunit (not depicted in the drawing) in the device 101 or the cloud server111, the obtained voice is converted into text and is then output to theprocessing portion 2000.

The processing portion 2000 is provided in the cloud server 111 (theserver 120) as described above and receives the information input by theinput portion 1000 of the device 101 and processes the information. Theprocessing portion 2000 includes a Japanese-English translating portion210A, a Japanese-English translating portion 210B, an English-Japanesetranslating portion 220A, an English-Japanese translating portion 220B,and a translation policy ranking portion 230.

The Japanese-English translating portion 210A (a policy A) performsJapanese-English translation of the original sentence (Japanese) 201input by the input portion 1000 in accordance with a policy A andobtains a translation sentence A (English) 211A. Then, theJapanese-English translating portion 210A outputs the translationsentence A (English) 211A to the English-Japanese translating portion220A.

The English-Japanese translating portion 220A (the policy A) performsEnglish-Japanese translation of the translation sentence A (English)211A output from the Japanese-English translating portion 210A inaccordance with the policy A and obtains a reverse translation sentenceA (Japanese) 221A. Then, the English-Japanese translating portion 220Aoutputs the reverse translation sentence A (Japanese) 221A to thetranslation policy ranking portion 230.

The Japanese-English translating portion (a policy B) 210B performs, inaccordance with a policy B, Japanese-English translation of the originalsentence (Japanese) 201 similar to the original sentence subjected totranslation in the Japanese-English translating portion 210A and obtainsa translation sentence B (English) 211B. Then, the Japanese-Englishtranslating portion 210B outputs the translation sentence B (English)211B to the English-Japanese translating portion 220B.

The English-Japanese translating portion 220B (the policy B) performsEnglish-Japanese translation of the translation sentence B (English)211B output from the Japanese-English translating portion 210B inaccordance with the policy B and obtains a reverse translation sentenceB (Japanese) 221B. Then, the English-Japanese translating portion 220Boutputs the reverse translation sentence B (Japanese) 221B to thetranslation policy ranking portion 230.

The translation policy ranking portion 230 ranks the translationpolicies.

Translation policy ranking is performed by sorting out the degrees ofsimilarity between the reverse translation sentences obtained by thepolicies and the original sentence, and ranking of the translationsentences is performed based on the ranking of the policies (depicted inFIG. 2B). Here, the Japanese-English translating portion 210A and theEnglish-Japanese translating portion 220A can perform bidirectionaltranslation and are collectively referred to as a bidirectionaltranslation subsystem 250A by the policy A, and the Japanese-Englishtranslating portion 210B and the English-Japanese translating portion220B can perform bidirectional translation and are collectively referredto as a bidirectional translation subsystem 250B by the policy B. Here,a method of sorting out the degrees of similarity is not limited to aparticular method. For example, a degree of similarity may be calculatedbased on the value obtained by subtracting the number of disparities(the sum of deletion and insertion) in units of characters from thenumber of matches in units of characters. A specific example ofcalculation of a degree of similarity will be described later.

The output displaying portion 3000 receives the information ranked bythe translation policy ranking portion 230 and displays a plurality oftranslation results in accordance with the ranking of translationpolicies. Moreover, the output displaying portion 3000 may display theplurality of translation results in accordance with the ranking andperform display urging the user to select an optimum translation result.A specific display example which is displayed by the output displayingportion 3000 will be described later. Here, the output displayingportion 3000 may be included, for example, in the device 101 providedwith the input portion 1000; if the device 101 provided with the inputportion 1000 is a device provided with no display portion, a deviceother than the device 101 may include the output displaying portion3000. If the processing portion 2000 and the output displaying portion3000 are not included in one apparatus, the output displaying portion3000 receives the results obtained by ranking performed by theprocessing portion 2000 and the translation results by an unillustratedcommunication unit and then displays the plurality of translationresults in accordance with the ranking of translation policies.

With such a configuration, by performing consistent translation andreverse translation for each of the plurality of translation policies,it is possible to perform ranking of translation policies by thetranslation policy ranking portion 230 and select a translation policythat well matches the original sentence for each input. Therefore, byusing a plurality of policies which are different in nature, it ispossible to deal with variations in input.

Here, if reverse translation of the translation sentence obtained by theJapanese-English translating portion 210A is performed by theEnglish-Japanese translating portion 220B or reverse translation of thetranslation sentence obtained by the Japanese-English translatingportion 210B is performed by the English-Japanese translating portion220A, it is possible to improve the accuracy of reverse translation,but, in this case, ranking of the translation sentence A and thetranslation sentence B, not ranking of the policy A and the policy B, isperformed, which is different from what is aimed by the presentdisclosure. By performing translation and reverse translation by aconsistent policy, it is expected that, for example, if translation issuccessfully performed by the policy A and translation is notsuccessfully performed by the policy B, reverse translation A is alsoperformed successfully and reverse translation B is also notsuccessfully performed. It can be expected that, when, in particular,translation is not successfully performed, since reverse translation ofthe unsatisfactory translation result is further performed, alower-quality translation result is obtained, which causes a greatdifference between the case in which translation is successfullyperformed and the case in which translation is not successfullyperformed.

Moreover, for example, even when there is a high possibility that a longsentence can be successfully translated by the policy A and a shortsentence can be successfully translated by the policy B, a certain longsentence can be successfully translated by the policy B depending on aninput sentence, which is the reason for selecting a translation policyfor each input. Incidentally, as for the translation policy, theabove-described rule-based translation and statistics-based translationmay be used for the policy A and the policy B. Moreover, a translationpolicy different from the policy A and the policy B may be used.Furthermore, even when both the policy A and the policy B arestatistics-based translation policies, it is simply necessary to makethe policy A and the policy B use different corpora based on which theamount of statistics is determined. That is, any translation policy maybe adopted unless the policy A and the policy B are one and the sametranslation policy.

In FIG. 3, a flowchart of the translation system in this embodiment isdepicted. With reference to this flowchart, the operation procedure ofthe translation system will be described by using an example ofJapanese-English translation.

First, the translation system obtains a Japanese original sentence to betranslated as an input (step S300). Next, the translation system obtainsa translation sentence A by performing Japanese-English translation ofthe original sentence by the policy A and then obtains a reversetranslation sentence A by performing English-Japanese translation of thetranslation sentence A by the policy A (step S310). Then, thetranslation system obtains a translation sentence B by performingJapanese-English translation of the original sentence by the policy Band then obtains a reverse translation sentence B by performingEnglish-Japanese translation of the translation sentence B by the policyB (step S320). Next, the translation system ranks the policy A and thepolicy B by using the original sentence, the reverse translationsentence A, and the reverse translation sentence B (step S330). Then,the translation system displays the translation results in accordancewith the policy ranking results (step S340). For example, if the policyA is ranked in the first place and the policy B is ranked in the secondplace by policy ranking, the translation system displays the translationsentence A which is the result of the Japanese-English translation bythe policy A in the first line of a translation result display area ofthe output displaying portion 3000 and displays the translation sentenceB which is the result of the Japanese-English translation by the policyB in the second line of the translation result display area.

In FIG. 4, a table for explaining the effect of combining the pluralityof policies of the translation system in this embodiment is depicted.

Assume that, for evaluating the performance of the translation system,for example, 100 sentences are prepared, translation by the policy A andtranslation by the policy B are performed, and the translation resultsare classified into correct translation and incorrect translation at thejudgment of an evaluator. In FIG. 4, a column 401 indicates thepercentage of input sentences in which both of the translation resultsby the policy A and the policy B are classified into correcttranslation, a column 404 indicates the percentage of input sentences inwhich both of the translation results by the policy A and the policy Bare classified into incorrect translation, a column 402 indicates thepercentage of input sentences in which only the results by the policy Bare classified into correct translation, and a column 403 indicates thepercentage of input sentences in which only the results by the policy Aare classified into correct translation, and the percentages are 74%,4%, 11%, and 14%.

Among them, the conditions of the column 401 and the column 404 are notimportant because the results indicate correct translation irrespectiveof the policy or the results indicate incorrect translation irrespectiveof the policy and the results are unaffected by the policy ranking. Whatis important is to operate the policy ranking in such a way that thepolicy outputting correct translation is highly ranked for theconditions of the column 402 and the column 403. Moreover, the higherthe percentage in the column 402 and the column 403, the greater theeffect of combining the policy A and the policy B.

In FIG. 5, a table illustrating the difference in an accuracy ratebetween a single policy and the combined use of policies of thetranslation system in this embodiment is depicted.

As for the ratio between correct translation and incorrect translationby the policy depicted in FIG. 4, the compilation thereof only for thepolicy A is listed in a column 405 and the compilation thereof only forthe policy B is listed in a column 406, and the accuracy rate obtainedwhen the policy A and the policy B are used together and the operationof the policy ranking is perfect is listed in a column 407; the ratiosare 88% and 85% and the accuracy rate is 96%. That is, there is apossibility that, even when the accuracy of translation on the order of80% is obtained by one policy, it is possible to obtain the accuracy oftranslation on the order of 90% by combining two policies.

In FIG. 6, a first translation example performed by the translationsystem in this embodiment is depicted.

In the first translation example, an input sentence is “Nagoya-eki madearuite dorekurai desuka?”. A translation sentence A by the policy A is“Is it how to walk to Nagoya Station?”, and a reverse translationsentence A is “Nagoya-eki made aruku hoho de aruka?”. Moreover, atranslation sentence B by the policy B is “How long does it take to walkto the Nagoya Station?”, and a reverse translation sentence B is“Nagoya-eki made aruite donokurai kakarimasuka?”. The degree ofsimilarity between the original sentence and the reverse translationsentence A is determined, and the degree of similarity between theoriginal sentence and the reverse translation sentence B is determined.Various methods have been known as the method for determining the degreeof similarity between sentences. For example, if the number ofdisparities (the sum of deletion and insertion) in units of charactersis subtracted from the number of matches in units of characters, as forthe policy A, the number of matches (9)−the number of disparities(8+5)=(−4) and, as for the policy B, the number of matches (14)−thenumber of disparities (3+6)=(5), and the degree of similarity of thepolicy B is higher than the degree of similarity of the policy A and, inthe translation policy ranking, the policy B is ranked in the firstplace and the policy A is ranked in the second place.

In FIG. 7, a second translation example performed by the translationsystem in this embodiment is depicted.

In the second translation example, an input sentence is “Kokyuso wohanteisuru sochi”. A translation sentence A by the policy A is “Devicethat determines respiratory cycles”, and a reverse translation sentenceA is “Kokyushuki wo ketteisuru sochi”. Moreover, a translation sentenceB by the policy B is “A device that meets the requirements of the testfor respiratory phases”, and a reverse translation sentence B is“Kokyuso no shiken no hitsuyojoken wo mitashiteirukoto wo sochi woteikyosuru”. The degree of similarity between the original sentence andthe reverse translation sentence A is determined, and the degree ofsimilarity between the original sentence and the reverse translationsentence B is determined. Various methods have been known as the methodfor determining the degree of similarity between sentences. For example,if the number of disparities (the sum of deletion and insertion) in unitof characters is subtracted from the number of matches in units ofcharacters irrespective of the order, as for the policy A, the number ofmatches (8)−the number of disparities (2+3)=(3) and, as for the policyB, the number of matches (8)−the number of disparities (2+21)=(−15), andthe degree of similarity of the policy A is higher than the degree ofsimilarity of the policy B and, in the translation policy ranking, thepolicy A is ranked in the first place and the policy B is ranked in thesecond place.

In the first translation example and the second translation example, thenatures of the input sentences are different and the translation policyranking results are also different.

In FIG. 8, an example of display of the first translation exampleperformed by the translation system in this embodiment is depicted. Forexample, in a translation sentence display area 801 of the device 101provided with the output displaying portion 3000, the translationsentences are displayed in the order corresponding to the translationpolicy ranking results. Here, the output displaying portion 3000 mayomit display of the translation sentence in the second place andtranslation sentences which are lower in rank. Moreover, if thetranslation sentence A and the translation sentence B are the samesentence, it is simply necessary to display one translation sentence andthere is no need to perform reverse translation and translation policyranking.

Furthermore, the device 101 may accept, by a touch operation or thelike, a selection of any one of a plurality of displayed translationresults from the user. That is, the user checks the display depicted inFIG. 8 and can select an intended sentence. Here, for example, in thecase of an application or the like that supports the conversationbetween people who use different languages by performing voice output ofthe translation results, the device 101 simply has to perform voiceoutput of the translation result selected by the user. When, inparticular, the present disclosure is applied to such an application,since the translation results are displayed in the order correspondingto the ranking results, the user can easily select a correct translationresult, which makes it possible to support smooth communication. Inaddition, if the user selects the translation result displayed in thefirst place but cannot communicate with the conversation partner, theuser simply has to select the translation result in the second place andmake the device 101 perform voice output, which allows the user to makethe device 101 perform voice output of the translation results indescending order of possibility.

Incidentally, in FIG. 8, only the plurality of translation sentenceresults of the translation performed by different policies are depicted,but the results of reverse translation may also be displayed near thecorresponding translation results. This allows the user to make aselection while checking whether or not the translation sentence in ahigher rank is surely close to his/her intended translation result.

Moreover, after accepting the selection made by the user, the policyranking calculation method (for example, calculation of the degree ofsimilarity described above) may be changed in accordance with theselection result. The ranking calculation method may be modified, forexample, if the user does not select the translation result which thesystem ranked in the first place a predetermined number of times ormore. This allows the system to learn the translation by the policy thatsuits the user in accordance with the habit of each user inconversation.

Incidentally, as the method of determining the degree of similaritybetween sentences, in addition to that described above, similarcalculation may be performed in units of words or, as for a disparityportion, a conceptual distance between words may be taken intoconsideration by using a thesaurus. Moreover, a word may be convertedinto a vector by language processing using statistical languageprocessing or a neural network and the degree of similarity betweenwords may be calculated as the degree of similarity between vectors.Furthermore, a vector corresponding to a sentence may be derived bycalculation of vectors in units of words and the degree of similaritybetween sentence expressions may be determined based on the degree ofsimilarity between vectors in units of sentences.

Incidentally, a case in which there are two translation policies A and Bis an example, and it is simply necessary to use two or more translationpolicies. Moreover, as for a language to be translated, a case in whichJapanese is translated into English is an example, and other languagesmay be used. Furthermore, since the bidirectional translation subsystemincluded in the system can perform translation from Japanese to Englishand translation from English to Japanese, by changing the order oftranslation, the translation system itself can perform translation fromEnglish to Japanese, which makes it possible to make the translationsystem function as a bidirectional translation system.

The technique described in the above-described embodiment can beimplemented in the following types of cloud service, for example.However, the type in which the technique described in theabove-described embodiment can be implemented is not limited to thetypes which will be described below.

Incidentally, it is assumed that any apparatus, program (recordingmedium incorporating a program), integrated circuit, and so forth whichreflect or incorporate any method described in the specification areincluded in the present disclosure.

(Service Type 1: Company's Data Center Type)

FIG. 9 depicts a service type 1 (a company's data center type). Thistype is a type in which the service provider 120 obtains informationfrom the group 100 and provides a service to the user. In this type, theservice provider 120 has the function of the data center operatingcompany 110. That is, the service provider 120 has the cloud server 111that manages big data. Therefore, the data center operating company 110does not exist.

In this type, the service provider 120 operates and manages a datacenter (the cloud server 111) (903). Moreover, the service provider 120manages an OS (902) and an application (901). The service provider 120provides a service by using the OS (902) and the application (901)managed by the service provider 120 (904).

(Service Type 2: IaaS Use Type)

FIG. 10 depicts a service type 2 (an IaaS use type). Here, IaaS is anabbreviation of infrastructure as a service and is a cloud serviceproviding model that provides an infrastructure itself for constructingand operating a computer system as a service provided via the Internet.

In this type, the data center operating company 110 operates and managesthe data center (the cloud server 111) (903). Moreover, the serviceprovider 120 manages the OS (902) and the application (901). The serviceprovider 120 provides a service by using the OS (902) and theapplication (901) managed by the service provider 120 (904).

(Service Type 3: PaaS Use Type)

FIG. 11 depicts a service type 3 (a PaaS use type). Here, PaaS is anabbreviation of platform as a service and is a cloud service providingmodel that provides a platform which is a base for constructing andoperating software as a service provided via the Internet.

In this type, the data center operating company 110 manages the OS (902)and operates and manages the data center (the cloud server 111) (903).Moreover, the service provider 120 manages the application (901). Theservice provider 120 provides a service by using the OS (902) managed bythe data center operating company 110 and the application (901) managedby the service provider 120 (904).

(Service Type 4: SaaS Use Type)

FIG. 12 depicts a service type 4 (an SaaS use type). Here, SaaS is anabbreviation of software as a service. For example, SaaS is a cloudservice providing model having the function of making it possible for acompany and an individual (user) without a data center (a cloud server)to use an application which is provided by a platform provider with adata center (a cloud server) via a network such as the Internet.

In this type, the data center operating company 110 manages theapplication (901), manages the OS (902), and operates and manages thedata center (the cloud server 111) (903). Moreover, the service provider120 provides a service by using the OS (902) and the application (901)managed by the data center operating company 110 (904).

As described above, in any type, it is assumed that the service provider120 provides a service. Moreover, for example, the service provider 120or the data center operating company 110 may develop a database or thelike of an OS, an application, or big data or outsource the developmentthereof to a third party.

This translation method can be industrially applied to a mobiletranslation terminal for tourists, a conversation assisting apparatusfor business operations in which foreign people take part, a foreignlanguage learning apparatus, a robot that can communicate with people inmultiple languages, and so forth.

What is claimed is:
 1. A translation method comprising: obtaining anoriginal sentence to be translated; performing bidirectional translationto obtain a translation sentence corresponding to the original sentenceby performing forward translation and obtaining a reverse translationsentence from the translation sentence by performing reversetranslation, consistently for each of a plurality of translationpolicies; ranking the translation policies based on a degree ofsimilarity between each of the reverse translation sentences by each ofthe plurality of translation policies and the original sentence; anddisplaying the each of translation sentences by each of the plurality oftranslation policies in a state in which each translation sentences isrelated to the ranking, wherein the forward translation and the reversetranslation are performed consistently for each translation policy. 2.The translation method according to claim 1, wherein in the performingbidirectional translation, if the original sentence is written in afirst language, a first translation sentence is obtained by translatingthe original sentence into a second language by a first translationpolicy, a first reverse translation sentence is obtained by performingreverse translation of the first translation sentence into the firstlanguage by the first translation policy, a second translation sentenceis obtained by translating the original sentence into the secondlanguage by a second translation policy, and a second reversetranslation sentence is obtained by performing reverse translation ofthe second translation sentence into the first language by the secondtranslation policy.
 3. The translation method according to claim 2,wherein in the ranking, a first degree of similarity between theoriginal sentence and the first reverse translation sentence iscalculated, a second degree of similarity between the original sentenceand the second reverse translation sentence is calculated, and the firstdegree of similarity and the second degree of similarity are comparedand the first translation sentence and the second translation sentenceare ranked in descending order of degree of similarity.
 4. Thetranslation method according to claim 3, wherein in the displaying, thefirst translation sentence and the second translation sentence ranked inthe ranking are displayed in such a way that a translation sentence in ahigher rank is displayed in an upper portion.
 5. The translation methodaccording to claim 1, wherein the degree of similarity is a valueobtained by subtracting a number of disparities in units of wordsbetween the reverse translation sentence and the original sentence froma number of matches in units of words between the reverse translationsentence and the original sentence.
 6. The translation method accordingto claim 1, wherein the translation policy is an algorithm reflecting adesign guide of machine translation.
 7. A translation system comprising:a processor; and a recording medium having stored therein instructionswhich, when executed by the processor, cause the processor to performoperations comprising: obtaining an original sentence to be translated,generating, for each of a plurality of translation policies, atranslation sentence corresponding to the original sentence byperforming forward translation and generates a reverse translationsentence from the translation sentence by performing reversetranslation, ranking the translation policies based on a degree ofsimilarity between the each of reverse translation sentences by each ofthe plurality of translation policies and the original sentence,displaying each of the translation sentences by each of the plurality oftranslation policies on a display in a state in which each translationsentence is related to the ranking, and wherein in generating,performing the forward translation and the reverse translationconsistently for each of translation policies.